Yuhan Ying

Shenyang Institute of Automation, University of Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yuhan Ying is a rising researcher at the intersection of robotics and medical imaging, whose work bridges precision engineering and computational diagnostics. Their primary contributions lie in two distinct but technically demanding fields: robotic tool center point (TCP) calibration and 3D medical image reconstruction. In robotics, Ying developed the posture-sequence particle swarm optimization (PS2O) algorithm, a novel method that dramatically improves TCP calibration accuracy by optimizing the condition number and eigenvalues of the regression matrix—a critical factor for industrial robot manipulation precision. This work, published in 2023, has already garnered 5 citations, signaling its relevance to the robotics community. In medical imaging, Ying introduced X-CTCANet, a deep learning framework that reconstructs 3D spinal CT images directly from 2D X-ray inputs, eliminating the need for multiple radiation-heavy scans. This 2024 publication, also with 5 citations, showcases Ying’s ability to apply advanced computational techniques to real-world clinical challenges. Though early in their career, Ying’s dual expertise in robotic calibration and medical image reconstruction positions them as a versatile innovator, with each paper already attracting attention from peers in both engineering and healthcare domains.